An auxiliary network is also used to generate a scanpath for a given stimulus by mainly leveraging the encoding ability of the encoder-decoder network. It consists of \(3 \times 3\)  convolutional layers, each activated by a \(ReLU\)  function. The last layer is composed of 100 features maps (i.e. 100 heatmaps), set in accordance to the number of fixation points per user of the considered dataset [1]} (see Section REF ).
\(Soft-Argmax\)  (SAM) [2]} is then used to estimate the coordinates of a fixation points from each feature map as follows :
\(SAM(x) = \sum _{i=0}^{W} \sum _{j=0}^{H} \frac{e^{\beta x_{i,j}}}{\sum _{i^\prime =0 }^{W} \sum _{j^\prime = 0 }^{H} e^{\beta x_{i^\prime ,j^\prime }}}({\frac{i}{W},\frac{j}{H}})^T\) 
